ASR Improve With XXLMConfig：muti-program-lanuage support ，usage in the doc or sample codes

[fengzhi09]

Background‌:

• ASR (Automatic Speech Recognition) can convert audio to text, but it's not suitable for all scenarios.
  For example, in the text "D7851次列车制动," the letter 'D' should be pronounced the same as the last character '动 (dong, 4th tone).'
• I can't simply increase the weight of the word 'D' when receiving audio input pronounced as 'dong (4th tone).'
• I'm considering introducing a Language Model (LM) into the final step of ASR (text generation) to automatically correct the output text.

What I've found in this project that may help me‌:

• There are two classes named 'OnlineLMConfig' and 'OfflineLMConfig,' which seem to be helpful.

• You can create instances of both classes in Java, but only 'OfflineLMConfig' is available in .NET（dotnet）or c-api.
  https://github.com/k2-fsa/sherpa-onnx/blob/master/sherpa-onnx/c-api/c-api.h#L117
  https://github.com/k2-fsa/sherpa-onnx/blob/master/sherpa-onnx/c-api/c-api.h#L440

• The documentation lacks details for both 'OnlineLMConfig' and 'OfflineLMConfig,' so I'm uncertain if they will truly solve my problem.

My suggestions‌:

1. Provide multi-programming-language support for XXLMConfig.
2. Include usage instructions for XXLMConfig in the documentation or provide sample codes.
3. Provide a simple, standard LM as a sample, similar to how VAD (Voice Activity Detection) was introduced into non-streaming ASR.